Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems

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Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems is …
instance of (P31):
scholarly articleQ13442814

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P8978DBLP publication IDjournals/bmcsb/BallnusHHGHT17
P6179Dimensions Publication ID1086152588
P356DOI10.1186/S12918-017-0433-1
P2888exact matchhttps://scigraph.springernature.com/pub.10.1186/s12918-017-0433-1
P932PMC publication ID5482939
P698PubMed publication ID28646868

P50authorJan HasenauerQ58209719
Fabian J. TheisQ39049575
P2093author name stringKathrin Hatz
Sabine Hug
Benjamin Ballnus
Linus Görlitz
P2860cites workEquation of State Calculations by Fast Computing MachinesQ5384234
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Integrative model of the response of yeast to osmotic shockQ40404592
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Using Bayesian-PBPK modeling for assessment of inter-individual variability and subgroup stratification.Q41692388
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P433issue1
P921main subjectMarkov chainQ176645
Markov chain Monte CarloQ1191869
P304page(s)63
P577publication date2017-06-24
P1433published inBMC Systems BiologyQ4835949
P1476titleComprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems
P478volume11

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Q92439720Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy
Q55514125Bayesian parameter estimation for biochemical reaction networks using region-based adaptive parallel tempering.
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